Systems and methods for automatically documenting an accident

ABSTRACT

A system for documenting an accident includes a vehicle that includes a transceiver device and a processing circuit. The processing circuit is configured to receive data from a collision detection device of the vehicle, determine, based on the received data, that an accident is impending or occurring involving the vehicle, generate a request for a nearby vehicle, and transmit, via the transceiver device, the request to the nearby vehicle. The request is for the nearby vehicle to illuminate a region associated with the accident, actively acquire data related to the accident, and record actively acquired data related to the accident.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/091,133, entitled “SYSTEMS AND METHODS FOR AUTOMATICALLY DOCUMENTINGAN ACCIDENT,” filed on Nov. 26, 2013, which is currently co-pending andincorporated herein by reference in its entirety and for all purposes.

BACKGROUND

Often, when a car accident occurs, the drivers involved in the accidentcall the police to document the accident. Each driver will give his orher side of events, and will attempt to provide relevant details, suchas the speed and direction that the cars were heading at the time of theaccident, etc. Based on these details, the police ultimately determinewho is at fault, and an insurance company will also make its owndetermination of fault based on the police report and driver statements.Frequently, a driver has little factual support, other than his or herstatements, in attempting to prove details related to the accident.

SUMMARY

One embodiment relates to a system for documenting an accident. Thesystem includes a vehicle comprising a transceiver device and aprocessing circuit. The processing circuit is configured to: receivedata from a collision detection device of the vehicle; determine, basedon the received data, that an accident is impending or occurringinvolving the vehicle; and generate a request for a nearby vehicle to:illuminate a region associated with the accident and actively acquiredata related to the accident; and record actively acquired data relatedto the accident. The processing circuit is further configured totransmit, via the transceiver device, the request to the nearby vehicle.

Another embodiment relates to a method of documenting an accident. Themethod includes: receiving data from a collision detection device of avehicle; determining, by a processing circuit, that based on thereceived data an accident is impending or occurring involving thevehicle; and generating a request for a nearby vehicle to: illuminate aregion associated with the accident and actively acquire data related tothe accident; and record actively acquired data related to the accident.The method further includes transmitting the request to the nearbyvehicle.

Another embodiment relates to a non-transitory computer-readable mediumhaving instructions stored thereon, that when executed by a computingdevice cause the computing device to perform operations for documentingan accident. The operations include: receiving data from a collisiondetection device of a vehicle; determining, based on the received data,that an accident is impending or occurring involving the vehicle; andgenerating a request for a nearby vehicle to: illuminate a regionassociated with the accident and actively acquire data related to theaccident; and record actively acquired data related to the accident. Theoperations further include transmitting the request to the nearbyvehicle.

Another embodiment relates to a system for documenting an accident. Thesystem includes a vehicle comprising a collision detection devicecomprising at least one of a radar device and a lidar device, where thecollision detection device is configured to illuminate and activelydetect a nearby vehicle, a storage device, and a processing circuit. Theprocessing circuit is configured to: receive data from the collisiondetection device; analyze the received data to detect an impending oroccurring accident, where the accident involves the nearby vehicle;determine, accident related data in response to the detected accident,where the accident related data is based on the received data; store theaccident related data in the storage device; and deliver the accidentrelated data to the nearby vehicle.

Another embodiment relates to a method of documenting an accident. Themethod includes: illuminating and actively detecting a nearby vehicleusing a collision detection device of a vehicle, where the collisiondetection device comprises at least one of a radar device and a lidardevice; receiving data from the collision detection device of thevehicle; analyzing, by a processing circuit, the received data to detectan impending or occurring accident, where the accident involves thenearby vehicle; determining accident related data in response to thedetected accident, where the accident related data is based on thereceived data; storing the accident related data in a storage device;and delivering the accident related data to the nearby vehicle.

Another embodiment relates to a non-transitory computer-readable mediumhaving instructions stored thereon, that when executed by a computingdevice cause the computing device to perform operations for documentingan accident. The operations include: illuminating and actively detectinga nearby vehicle using a collision detection device of a vehicle, wherethe collision detection device comprises at least one of a radar deviceand a lidar device; receiving data from the collision detection deviceof the vehicle; analyzing the received data to detect an impending oroccurring accident, where the accident involves the nearby vehicle;determining accident related data in response to the detected accident,where the accident related data is based on the received data; storingthe accident related data in a storage device; and delivering theaccident related data to the nearby vehicle.

Another embodiment relates to a system for documenting an accident. Thesystem includes a vehicle comprising a collision detection device, anearby vehicle detection device, a storage device, and a processingcircuit. The processing circuit is configured to: receive data from thenearby vehicle detection device, wherein the data includes data relatedto a nearby vehicle; receive data from the collision detection device;determine, based on the received data from the collision detectiondevice, that an accident is impending or occurring involving thevehicle; analyze the received data from the nearby vehicle detectiondevice to detect an ID of the nearby vehicle; and store the detected IDin the storage device.

Another embodiment relates to a method of documenting an accident. Themethod includes: receiving data from a nearby vehicle detection deviceof a vehicle, wherein the data includes data related to a nearbyvehicle; receiving data from a collision detection device of thevehicle; determining, by a processing circuit, that based on thereceived data from the collision detection device an accident isimpending or occurring involving the vehicle; analyzing the receiveddata from the nearby vehicle detection device to detect an ID of thenearby vehicle; and storing the detected ID in a storage device.

Another embodiment relates to a non-transitory computer-readable mediumhaving instructions stored thereon, that when executed by a computingdevice cause the computing device to perform operations for documentingan accident. The operations include: receiving data from a nearbyvehicle detection device of a vehicle, wherein the data includes datarelated to a nearby vehicle; receiving data from a collision detectiondevice of the vehicle; determining that based on the received data fromthe collision detection device an accident is impending or occurringinvolving the vehicle; analyzing the received data from the nearbyvehicle detection device to detect an ID of the nearby vehicle; andstoring the detected ID in a storage device.

The foregoing summary is illustrative only and is not intended to be inany way limiting. In addition to the illustrative aspects, embodiments,and features described above, further aspects, embodiments, and featureswill become apparent by reference to the drawings and the followingdetailed description.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a block diagram of a system for documenting an accidentaccording to one embodiment.

FIG. 2 is a block diagram of a system for documenting an accidentaccording to one embodiment.

FIG. 3 is a block diagram of a processing circuit according to oneembodiment.

FIG. 4 is a schematic diagram of a system for documenting an accidentaccording to one embodiment.

FIG. 5 is a flowchart of a process for documenting an accident accordingto one embodiment.

FIG. 6 is a flowchart of a process for documenting an accident accordingto one embodiment.

FIG. 7 is a flowchart of a process for documenting an accident accordingto one embodiment.

FIG. 8 is a flowchart of a process for documenting an accident accordingto one embodiment.

FIG. 9 is a flowchart of a process for documenting an accident accordingto one embodiment.

FIG. 10 is a flowchart of a process for documenting an accidentaccording to one embodiment.

FIG. 11 is a flowchart of a process for documenting an accidentaccording to one embodiment.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings, which form a part hereof. In the drawings,similar symbols typically identify similar components, unless contextdictates otherwise. The illustrative embodiments described in thedetailed description, drawings, and claims are not meant to be limiting.Other embodiments may be utilized, and other changes may be made,without departing from the spirit or scope of the subject matterpresented here.

Referring generally to the figures, various embodiments of systems andmethods for documenting an accident are shown and described. It is oftenthe case that when a car accident occurs, the drivers involved areprimarily responsible for providing the details of the accident. Forexample, a driver may be required to recall a speed of his vehicle (car,truck, motorcycle, etc.) and a direction the vehicle was travelling atthe time of the accident. However, these details are reliant on thedriver's recollection of the accident, and the driver may not have beenpaying close attention to such details when the accident occurred.

According to various embodiments, a processing circuit is utilized torequest and/or automatically record data related to a vehicularaccident. For example, a car that is involved in an accident can detectthat the accident is impending or occurring, and the processing circuitof the car can generate a request for a nearby vehicle (i.e. a “witness”vehicle) to record data related to the accident. By doing so, the nearbyvehicle can provide a witness perspective of the accident, and the datarecorded can be used in determining liability, damages, etc. The nearbyvehicle can be equipped with radar or lidar systems that generate datarelated to the position, direction of motion, speed, orientation, and/orcontour of vehicles involved in the accident. The nearby vehicle canalso record specific timing information related to the accident. Anyrecorded data may be stored by a storage system of the nearby vehicle,the data may be transmitted back to the car that generated the request,or the data may be transmitted to a remote location (e.g., a website,online storage, etc.). As another example, a car may be equipped with aprocessing circuit configured to detect an accident that is impending oroccurring that involves other vehicles (and not the car). Upon detectingthe accident of the other vehicle(s), the car can automatically generatedata related to the accident (e.g., using radar or lidar systems of thecar), and the accident related data may then be stored or transmitted.Additionally, the processing circuit of any of the embodiments hereinmay be used to determine and store ID information (e.g., license platenumbers, RFID tag information, etc.) related to a vehicle involved in orwitnessing an accident, as will be discussed further herein. Forexample, a car that is involved in an accident may automatically detectand record ID information of a nearby witness vehicle. The car may use acamera, an RFID sensor, radar, lidar, or other collision detectionsystems/devices of the vehicle to detect the ID information. Forexample, images from a camera may be analyzed to determine license plateinformation. As another example, an RFID sensor may be used to determinean RFID tag of a nearby vehicle. It should be understood that althoughthis disclosure often refers to a “nearby vehicle,” interactions withmultiple nearby vehicles are within the scope of the presentapplication.

Referring to FIG. 1 a block diagram of system 100 for documenting anaccident is shown. According to one embodiment, system 100 includesprocessing circuit 102 and transceiver device 104. System 100 may alsoinclude sensor device 106. Processing circuit 102 is generallyconfigured to interface with an accident detection system of a vehicle.For example, processing circuit 102 may receive real-time data from theaccident detection system. In one embodiment, the accident detectionsystem includes camera, radar, and/or lidar devices. Such camera, radar,and lidar devices generally provide data related to thedirection/orientation of detected objects, the contour of objects, andthe motion of objects (e.g., vehicles on the road, etc.). Based on theinformation from the camera, radar, and/or lidar devices, the accidentdetection system or processing circuit 102 can determine that anaccident that involves the vehicle is impending or occurring. Inresponse to such a detected accident, processing circuit generates arequest to be transmitted to a nearby vehicle, where the request is forthe nearby vehicle to record details related to the accident. Therequest may be transmitted via transceiver device 104. The request maybe selectively transmitted only to a specific nearby vehicle or a set ofnearby vehicles, or may be transmitted (i.e., broadcast) for receptionby all nearby vehicles. Transceiver device 104 includes all componentsnecessary to transmit and receive data. For example, transceiver device104 may include a radiofrequency transmitter and a radiofrequencyantenna, etc. In some embodiments, system 100 includes sensor device106, which is generally configured to provide data related to an ID of anearby vehicle. For example, sensor device 106 may include a cameraconfigured to provide video data. From the video data, processingcircuit 102 may determine a license plate number of a nearby vehicle. Asanother example, sensor device 106 may include an RFID sensor configuredto provide RFID data. From the RFID data, processing circuit 102 maydetermine an RFID tag of a nearby vehicle. The RFID tag may includelicense plate information, or other identification information.

Referring to FIG. 2 a block diagram of system 200 for documenting anaccident is shown. According to one embodiment, system 200 includesprocessing circuit 202, collision detection device 204, and storagedevice 206. System 200 may also include transceiver device 208.Processing circuit 202 is generally configured to interface withcollision detection device 204 to detect an impending or occurringaccident involving other vehicles. Collision detection device 204 isconfigured to provide radar and/or lidar data related to objects (i.e.nearby vehicles) detected using radar or lidar signals, respectively.Collision detection device 204 includes all components necessary (e.g.,one or more sensors integrated or coupled to the vehicle) to generatesuch data and provide the data to processing circuit 202. Processingcircuit 202 analyzes the radar and/or lidar data provided to detect anaccident. Upon detecting the accident, processing circuit 202 determinesrelevant details related to the accident (e.g., position of a vehicle,direction of motion of a vehicle, speed of a vehicle, angular motion ofa vehicle, orientation of a vehicle, etc.). The details related to theaccident may then be stored in storage device 206, which includescomponents necessary to store data (e.g., physical hard drives, flashstorage, etc.). Additionally, processing circuit 202 may store raw radarand/or lidar data from collision detection device 204. In someembodiments, system 200 includes transceiver device 208, which includesall components necessary to transmit and receive data. Any stored dataand any data generated by collision detection device 204 and processingcircuit 202 may be transmitted via transceiver device 208.

Referring to FIG. 3, a block diagram of processing circuit 300 forcompleting the systems and methods of the present disclosure is shownaccording to one embodiment. Processing circuit 300 is generallyconfigured to communicate with a collision detection system (e.g.,collision detection device 204) of a vehicle. Processing circuit 300 cananalyze data provided by the collision detection system to determinethat an accident has occurred or is about to occur involving the vehicleor other additional vehicles. In some embodiments, processing circuit300 is configured to generate a request to be transmitted to a nearbyvehicle. The request is for the nearby vehicle to illuminate theaccident scene with radar or lidar probe beams and to hence activelyacquire radar or lidar data related to the accident. The requestadditionally is for the nearby vehicle to record actively acquired radaror lidar data related to the accident. The request for recorded data mayencompass both the data acquired in response to the request, as well aspreviously acquired data concerning the accident (e.g., concerning thelocation, the requesting vehicle or additional vehicles in thevicinity). Processing circuit 300 may accept input data continuously orperiodically. Processing circuit 300 also generates metadata to beincluded as part of a request. Any of the data generated by processingcircuit 300 may also be based on user input or configuration data. Inanalyzing data from the collision detection system (e.g., camera, RFID,radar, or lidar data), and in generating a request to be transmitted,processing circuit 300 may make use of machine learning, artificialintelligence, interactions with databases and database table lookups,pattern recognition and logging, intelligent control, neural networks,fuzzy logic, etc. Processing circuit 300 further includes input 302 andoutput 304. Input 302 is configured to receive a data stream (e.g., adigital or analog stream of data) and configuration information. Output304 is configured to output data for transmission (e.g., a request to betransmitted) or for use in a configuration process of a device havingprocessing circuit 300.

According to one embodiment, processing circuit 300 includes processor306. Processor 306 may be implemented as a general-purpose processor, anapplication specific integrated circuit (ASIC), one or more fieldprogrammable gate arrays (FPGAs), a digital-signal-processor (DSP), agroup of processing components, or other suitable electronic processingcomponents. Processing circuit 300 also includes memory 308. Memory 308is one or more devices (e.g., RAM, ROM, Flash Memory, hard disk storage,etc.) for storing data and/or computer code for facilitating the variousprocesses described herein. Memory 308 may be or may includenon-transient volatile memory or non-volatile memory. Memory 308 mayinclude database components, object code components, script components,or any other type of information structure for supporting the variousactivities and information structures described herein. Memory 308 maybe communicably connected to processor 306 and provide computer code orinstructions to processor 306 for executing the processes describedherein (e.g., the processes shown in FIGS. 5-10). Memory 308 includesmemory buffer 310. Memory buffer 310 is configured to receive a datastream from a user input and/or components of a collision detectionsystem through input 302. For example, the data may include inputrelated to radar information or lidar information that was generated bythe collision detection system. The data received through input 302 maybe stored in memory buffer 310 until memory buffer 310 is accessed fordata by the various modules of memory 308. For example, analysis module316 can access the data that is stored in memory buffer 310. Any datareceived through input 302 may also be immediately accessed.

Memory 308 further includes configuration data 312. Configuration data312 includes data related to processing circuit 300. For example,configuration data 312 may include information related to interfacingwith other components (e.g., components of a collision detection system,etc.). This may also include the command set needed to interface with acomputer system used configure a system having processing circuit 300.This may also include the command set needed to generate a userinterface or to communicate with other user interface components of thevehicle (e.g., a touch screen display, etc.). Based on data stored inconfiguration data 312, processing circuit 300 may format data foroutput via output 304, which may include formatting data fortransmission, etc. For example, processing circuit 300 may generate arequest and format the request to be transmitted via a radiofrequencytransceiver. Processing circuit 300 may also format data fortransmission according to any protocols or standards as specified byconfiguration data 312. Configuration data 312 may further includeinformation as to how often input should be accepted from a collisiondetection system. Configuration data 312 may include default valuesrequired to initiate communication with any components of the systemhaving processing circuit 300. Configuration data 312 further includesdata to configure communication between the various components ofprocessing circuit 300. Memory 308 further includes preference data 314,which is configured to store various user preferences and settingsrelated to the systems described herein. For example, the describedsystems may be enabled or disabled by a user as specified by preferencedata 314.

Memory 308 further includes analysis module 316. Analysis module 316 isconfigured to receive data from a collision detection system of avehicle (e.g., collision detection device 204) and to determine whetheran accident is impending/occurring involving the vehicle or anothernearby vehicle. Analysis module 316 may determine the accident based onthe data provided, or analysis module 316 may be provided an indicatorfrom collision detection system specifying that the collision detectionsystem has detected the accident. Analysis module 316 also may accessconfiguration information and other data as provided by processingcircuit 300. In one embodiment, analysis module 316 instructs requestmodule 318 to generate a request to be transmitted to nearby vehicles.

In one embodiment, analysis module 316 determines if an accidentinvolving the vehicle having processing circuit 300 is impending or isoccurring. Analysis module 316 determines the accident by analyzing thedata provided from the collision detection system of the vehicle.Analysis module 316 may also access other sensor data (e.g., cameras)and systems of the vehicle to determine operational characteristics ofthe vehicle (e.g., current speed, current direction, etc.). Thecollision detection system of the vehicle is generally equipped withradar and/or lidar detection devices. The detection devices generallyscan the area around the vehicle and provide information related toobjects as discerned from reflected radar and/or lidar signals. Based onthese signals, analysis module 316 may decide whether an accident isabout to occur, or if the accident is already occurring or has occurred.For example, analysis module 316 may determine that another vehicle is10 feet in front of the vehicle and is moving 40 mph more slowly thanthe vehicle is moving. Based on those characteristics, analysis module316 may conclude that a collision is imminent. As another example,analysis module 316 may detect a sudden change in velocity of thevehicle or another vehicle. As another example, analysis module 316 maydetermine that another vehicle (or object) is less than a foot from thevehicle, and thus, an accident is occurring, or has occurred. Indetermining an accident, analysis module 316 may access a prioriknowledge relating to the vehicle. For example, analysis module 316 mayaccess configuration data 312 for braking capabilities, steering andhandling capabilities, contour and dimension information, weightinformation, acceleration/deceleration characteristics, etc. Upondetecting an accident, analysis module 316 can direct request module togenerate a request to be transmitted to a nearby vehicle so the nearbyvehicle acquires and records information related to the accident.

In one embodiment, the collision detection system of the vehicleincludes additional sensor devices that provide data to be analyzed byanalysis module 316. For example, the collision detection system mayinclude a camera (that captures still images or video), and analysismodule 316 may determine that an accident is in progress or hasoccurred, in part, based on the position or motion of a proximatevehicle that is detected. As another example, the collision detectionsystem may include a microphone device, and analysis module 316 maydetermine that an accident is in progress or has occurred, in part,based on a loud braking noise or collision noise that is detected. Asanother example, the collision detection system may interface with thebraking systems of the vehicle provide information related to the brakesas they are applied by the driver (e.g., pressures, braking lengths,etc.). As another example, the collision detection system may interfacewith an airbag system of the vehicle, and analysis module 316 may basean accident determination on whether an airbag has been deployed. Asanother example, the collision detection system may include anaccelerometer, and analysis module 316 may base an accidentdetermination on acceleration/deceleration values.

In one embodiment, analysis module 316 records ID information related tonearby vehicles (e.g., witness vehicles). A vehicle may be equipped witha nearby vehicle detection device capable of detecting nearby vehicles.The nearby vehicle detection device may be separate from or part of acollision detection system (e.g., collision detection device 204) of thevehicle. For example, the vehicle may have a camera system that providesimage data to analysis module 316. Analysis module 316 may analyze theimage data to determine a license plate number of a vehicle. Analysismodule 316 may make use various optical character recognition algorithmsin detecting a license plate number. Alternatively, analysis module 316may use object recognition algorithms to detect a perimeter of thelicense plate, and store an image including the license plate. Asanother example, a vehicle may be equipped with an RFID scanning systemthat provides data to analysis module 316. Based on the RFID data,analysis module 316 may determine ID information for a vehicle. Forexample, the RFID data may include information for a detected RFID tagof a nearby vehicle. The RFID tag may include the license plate number,or any other identification information for the nearby vehicle (e.g., aVIN number, make and model information, a driver's license number,etc.). Any ID information determined by analysis module 316 may bestored in a storage system of the vehicle (e.g., in memory 308, a harddisk, flash memory, etc.), or it may be transmitted (via a transceiverdevice). Additional information that is related to the nearby vehiclemay also be determined. For example, analysis module 316 may processinformation from radar and/or lidar systems of the vehicle to determinethe position, direction of motion, speed, orientation, and/or contour ofa nearby vehicle. The additional information may be stored and/ortransmitted along with the ID information. In one embodiment, analysismodule 316 analyzes data from a collision detection device of thevehicle to determine whether or not a nearby vehicle was involved in theaccident. A determination that the nearby vehicle was not involved inthe accident may precede any additional ID information analysis relatedto the nearby vehicle (e.g., the nearby vehicle may be required to be anuninvolved witness vehicle, etc.). Any of the analysis described hereinmay also be responsive to a determination that an accident is impendingor occurring. In one embodiment, the nearby vehicle is one to which arequest as described herein was transmitted (e.g., a request toilluminate a region associated with the accident, to actively acquiredata related to the accident, and to record the actively acquired datarelated to the accident, etc.).

In one embodiment, analysis module 316 receives data from a collisiondetection device of the vehicle. As discussed above, the collisiondetection device generally contains one or more radar and/or lidardevices, and may contain additional sensors and components (e.g.,cameras, ultrasonic sensors, microphones, etc.). Analysis module 316analyzes the data from the collision detection device to detect anaccident (impending, accruing, or occurred) involving another nearbyvehicle (or vehicles). For example, analysis module 316 may analyzeradar information to determine that a vehicle in the next lane hasrapidly reduced its velocity (e.g., if the driver of the nearby vehicleengaged the brakes, etc.). As another example, analysis module 316 mayanalyze radar information to determine that two vehicles' projectedpaths will collide in a certain amount of time. Analysis module 316 mayalso detect an accident involving other vehicles by interfacing theadditional sensors and components of the collision detection device. Forexample, analysis module 316 may receive audio information and detect anearby collision sound. As another example, analysis module 316 mayreceive camera information and analyze images provided by the camera inconjunction with radar information. Any combination of data (e.g., lidardata and camera data, radar data and audio data, etc.) may be used indetecting an accident. Upon detecting an accident, analysis module 316module may automatically record data related to the accident (e.g., instorage device 206, etc.). Analysis module 316 may record all data(e.g., raw data from all radar or lidar devices), may detect processeddata (e.g., position or motion parameters derived from raw data), or mayselect relevant data (e.g., only data from certain sensors/devices). Inone embodiment, analysis module 316 causes processing circuit 300 toaccept data at a maximum possible data rate from the various devicesdiscussed herein. Analysis module 316 may also encrypt any data that isstored, and an encryption standard and encryption key may be specifiedby configuration data 312 or preference data 314.

Analysis module 316 may determine and record specific types of databased on the data received from the collision detection device. In oneembodiment, analysis module 316 determines position coordinates of anearby vehicle. Analysis module 316 may access GPS or mappinginformation of the vehicle having processing circuit 300 (e.g. from aGPS system or mapping application of the vehicle), and analysis module316 may store those coordinates along with distance and directioninformation based on a radar or lidar signal. The coordinates of thenearby vehicle may then be calculated based on the distance anddirection the nearby vehicle is from the vehicle. In one embodiment,analysis module 316 determines the velocity and orientation informationof the nearby vehicle. In one embodiment, analysis module 316 determinestiming information that is stored along with any other determined data.The timing information may be stored with a high precision (e.g.,including milliseconds, microseconds, nanoseconds, etc.). Any data thatis described herein may be time stamped such that a precise sequence ofevents may be recreated upon later analysis of stored data. In oneembodiment, analysis module 316 determines contour information relatedto the nearby vehicle. Such information may be compared to a database ofvehicle model information (stored by storage systems of the vehicle, orremotely accessed) to determine a likely make and model of the nearbyvehicle.

In one embodiment, analysis module 316 may determine that an accidenthas or is about to occur, at least partially in response to receiving arequest to acquire and record data from a requesting vehicle. Forexample, in an embodiment having a transceiver device (e.g., transceiverdevice 208), which may be a radiofrequency transmitter, the request maybe received by the transceiver device. Upon receipt of the request,analysis module 316 may actively acquire (i.e., by use of illuminationand sensing with radar or lidar sensors) and record data from thecollision detection device. Analysis module 316 may also analyze therequest, which may include identification or positioning information sothat analysis module 316 can determine a precise location of which tomonitor (e.g., which car to monitor, whether the requesting vehicle orthe referenced accident site is on the left side or right side of thecar, etc.). Additionally, the request may specify that any recorded datashould be transmitted back to the requesting vehicle, or to anotherlocation. Analysis module 316 may interface with the transceiver deviceand provide the signals necessary so that any accident related datagenerated by analysis module 316 is transmitted in accordance with therequest. For example, analysis module 316 may cause the transceiverdevice to emit a radiofrequency signal to wirelessly transmit therecorded accident related data.

Request module 318 is configured to generate a request for a nearbyvehicle, and to control the transmission of the request. The request isfor the nearby vehicle to actively acquire (by illuminating a regionassociated with the accident using radar or lidar probe signals andsensing with radar or lidar sensors) and record information related toan accident involving the requesting vehicle. Request module 318generates such a request in response to analysis module 316, whichdetects the accident as it is in progress or is impending, and instructsrequest module 318 to transmit the request. Request module 318 mayinclude specific instructions and metadata in the request. Requestmodule 318 generates the signals necessary to control a transceiverdevice (e.g., transceiver device 104) such that the request istransmitted. A request may be transmitted according to any protocol,frequency, or standard which may be predefined and set by configurationdata 312 or preference data 314.

In one embodiment, request module 318 generates a request that specifiesthat all available data should be actively acquired and recorded by anearby vehicle receiving the request (the “witness” vehicle).Alternatively, the request may specify that only certain types of datashould be recorded. For example, the request may specify that radarinformation or lidar information is desired. The request may specifythat only data related to the requesting vehicle is desired. The requestmay specify that data related to additional vehicles is also desired.The request may specify that data related to a particular site (i.e.,that of the actual or predicted accident) is desired. The request mayspecify a time window for the recorded data (e.g., only that acquiredafter the request, previously acquired data, both new and previouslyacquired data, etc.). The request may specify that the witness vehicleadditionally acquire and/or record data from passive sensors (e.g.,cameras, microphones, etc.). The request may specify that the witnessvehicle record identification data regarding the witness vehicle, itsoperator, or its owner. The request may ask the witness vehicle toacknowledge receipt of the request, to explicitly accept or refuse therequest, to report an inability to acquire or record the data, etc. Therequest may specify that the witness vehicle should store positioningcoordinates of the witness vehicle or any other detected vehicles. Therequest may specify that the witness vehicle store the velocity(translational and/or angular) and orientation of the witness vehicle orof other vehicles as detected by the witness vehicle. The request mayspecify that the witness vehicle contour information other vehicles asdetected by the witness vehicle. The request may specify that thewitness vehicle store timing information related to the accident so thatany other data stored may be synced.

In one embodiment, request module 318 generates metadata to be includedwith a request. The metadata may include any number of data itemsrelated to the vehicle having the accident. For example, the metadatamay include positioning coordinates, velocity and orientationinformation, insurance information (e.g., policy number, insurancecompany), contact information for an operator/driver of the vehicle(e.g., a phone number, name, address, etc.), an internet address,payment information, a timestamp of when the request was generated,and/or a vehicle ID (e.g., license plate number, VIN number, driver'slicense number, etc.). If insurance information is included, suchinformation may be used by the witness vehicle so that the properinsurance company can be contacted and/or provided the recorded data. Ifcontact information is included it may be used so that the driver can beprovided the recorded data or so that the driver can be notified thatthe accident related data has been recorded. The request may also directthe witness vehicle to automatically transmit the recorded data to anexternal storage location (e.g., a website, a cloud storage service, anFTP site, an email address, etc.) as dictated by the internet address.In one scenario, a witness vehicle may record data or provide access torecorded data for a price. In such a scenario, payment information andan offered price may be included in the request. A price that the driveris willing to pay to have data recorded by a witness vehicle may bepreviously specified (e.g., by preference data 314). After a request isgenerated, it is then transmitted by a transceiver.

In one embodiment, a request includes instructs a witness vehicle totransmit any recorded data back to the requesting vehicle. For example,transceiver device 104 may be used to send the request, and receive anyresponse data (including recorded accident data, ID information for thewitness vehicle, etc.) from the witness vehicle. In this manner, a copyof the recorded data may be received and stored on a storage device ofthe requesting vehicle.

Referring to FIG. 4, a schematic diagram of a vehicle 400 is shownaccording to one embodiment. Vehicle 400 has a system for documenting anaccident (e.g., system 100 or system 200). Vehicle 400 includesprocessing circuit 402, collision detection device 404 (which is shownas having multiple components), transceiver 406, and storage device 408.Collision detection device 404 may have any number of radar device andlidar devices integrated throughout vehicle 400. For example, vehicle400 may have radar antennas at the front, rear, left and right ofvehicle 400. As another example, vehicle 400 may have a radar or lidardevice on the roof of vehicle 400, such that the radar or lidar devicemay scan in 360 degrees. Collision detection device 404 may also includeother sensing devices, such as one or more cameras, ultrasonic devices,microphones, and RFID sensors. Vehicle 400 further includes storagedevice 408. Storage device 408 may include one or more hard drives,flash drives, optical drives, and any other storage devices capable ofstoring data.

Referring to FIG. 5, a flow diagram of a process 500 for documenting anaccident is shown, according to one embodiment. In alternativeembodiments, fewer, additional, and/or different actions may beperformed. Also, the use of a flow diagram is not meant to be limitingwith respect to the order of actions performed. Data is received from acollision detection device of a vehicle (502). For example, the vehiclemay have various collision detection devices integrated into thevehicle, including radar, lidar, camera, and/or ultrasonic devices.Based on the data from the collision detection device, an accidentinvolving the vehicle is determined to be occurring or impending (504).A request is generated (506) and transmitted (508) to another nearbyvehicle (e.g. a witness vehicle). The request is for the nearby vehicleto actively acquire and to record data related to the accident (i.e.from the perspective of the nearby vehicle).

Referring to FIG. 6, a flow diagram of a process 600 for documenting anaccident is shown, according to one embodiment. In alternativeembodiments, fewer, additional, and/or different actions may beperformed. Also, the use of a flow diagram is not meant to be limitingwith respect to the order of actions performed. Data is received from acollision detection device of a vehicle (602). Based on the data fromthe collision detection device, an accident involving the vehicle isdetermined to be occurring or impending (604). A request is generated(606) to be transmitted to a nearby vehicle. The request is for thenearby vehicle to actively acquire and to record data related to theaccident. Metadata is generated (608) to be included with the request.The metadata may include various data items related to the vehiclehaving the accident and transmitting the request. For example, themetadata may include position coordinates (e.g., GPS data, mapping data,etc.) (610), velocity and/or orientation information (612), insuranceinformation (e.g., insurance company, policy number, etc.) (614),contact information (e.g., name, address, phone number, email, etc.)(616), payment information (e.g., for a fee paid to the operator of thenearby vehicle for recording the data) (620), timestamp data (622), andthe vehicle's ID information (license plate number, VIN number, make andmodel, etc.) (624). The metadata may also include an internet address(618) to which any recorded data should be sent. For example, therequest may specify that the nearby vehicle (that recorded the accidentrelated data) should upload the recorded data to a certain website, FTPsite, online storage service, etc., as defined by the internet address.The request and metadata are transmitted (626) to the nearby vehicle.

Referring to FIG. 7, a flow diagram of a process 700 for documenting anaccident is shown, according to one embodiment. In alternativeembodiments, fewer, additional, and/or different actions may beperformed. Also, the use of a flow diagram is not meant to be limitingwith respect to the order of actions performed. Data is received from acollision detection device of a vehicle (702). Based on the data fromthe collision detection device, an accident involving the vehicle isdetermined to be occurring or impending (704). A request is generated(706) and transmitted (708) to a nearby vehicle. The request is for thenearby vehicle to actively acquire and to record data related to theaccident. Any recorded data related to the accident may then be receivedby the vehicle that had the accident (710). The received data related tothe accident is stored (712) in a storage device in the vehicle (e.g., ahard drive, a flash drive, etc.).

Referring to FIG. 8, a flow diagram of a process 800 for documenting anaccident is shown, according to one embodiment. In alternativeembodiments, fewer, additional, and/or different actions may beperformed. Also, the use of a flow diagram is not meant to be limitingwith respect to the order of actions performed. Data is received from acollision detection device of a vehicle (802). The received data isanalyzed (804) to detect an accident involving a nearby vehicle. If anaccident is detected to be occurring or impending, accident related datais determined based on the received data (806). For example, theaccident related data may include positioning coordinates (e.g., GPSinformation, mapping information, etc.) (808) of a vehicle involved inthe accident. As another example, the accident related data may includevelocity and orientation information (810) of a vehicle involved in theaccident. As another example, the accident related data may includetiming information (812) related to a vehicle involved in the accident.As another example, the accident related data may include contourinformation (814) of a vehicle involved in the accident. The accidentrelated data is stored (816) in a storage device. The accident relateddata is delivered to the nearby vehicle (818).

Referring to FIG. 9, a flow diagram of a process 900 for documenting anaccident is shown, according to one embodiment. In alternativeembodiments, fewer, additional, and/or different actions may beperformed. Also, the use of a flow diagram is not meant to be limitingwith respect to the order of actions performed. Data is received from acollision detection device of a vehicle (902). The received data isanalyzed (904) to detect an accident involving a nearby vehicle. If anaccident is detected to be occurring or impending, accident related datais determined based on the received data (906). In addition, an ID ofthe nearby vehicle is determined (908). For example, the vehicle mayinclude a camera system that can detect a license plate number of thenearby vehicle. As another example, the vehicle may include an RFIDsensor system that can detect an RFID tag of the nearby vehicle. Theaccident related data and determined ID are stored (910) in a storagedevice. The accident related data and ID are delivered to the nearbyvehicle (912).

Referring to FIG. 10, a flow diagram of a process 1000 for documentingan accident is shown, according to one embodiment. In alternativeembodiments, fewer, additional, and/or different actions may beperformed. Also, the use of a flow diagram is not meant to be limitingwith respect to the order of actions performed. A request is received ata vehicle, where the request is sent from a nearby vehicle and is forthe vehicle to actively acquire and to record data related to theaccident. In response to the request, data is received from a collisiondetection device of a vehicle (1004). The received data is analyzed(1006) to detect an accident involving the nearby vehicle. Accidentrelated data is determined based on the received data (1008). Inaddition, an ID of the nearby vehicle is determined (1010). The accidentrelated data and determined ID are stored (1012) in a storage device.The initial request may also specify that the data should be transmittedaccording to the instructions of the request. In this situation, theaccident related data is transmitted (1014). For example, the accidentrelated data may be transmitted to the nearby vehicle that requested thedata. As another example, the accident related data may be transmittedto a remote storage location (e.g., an FTP site, a website, a cloud datastorage service, etc.).

Referring to FIG. 11, a flow diagram of a process 1100 for documentingan accident is shown, according to one embodiment. In alternativeembodiments, fewer, additional, and/or different actions may beperformed. Also, the use of a flow diagram is not meant to be limitingwith respect to the order of actions performed. Data is received from acollision detection device of a vehicle (1102). The collision detectiondevice may include one or more cameras, accelerometers, microphones,radar device, and/or lidar devices, etc. The received data from thecollision detection device includes data related to the vehicle (e.g.,collision data, sensor data, speed data, brake system data, etc.). Datais received from a nearby vehicle detection device of a vehicle (1104).The nearby vehicle detection device may include one or more cameras,RFID sensors, radar devices, lidar devices, etc. The received data fromthe nearby vehicle detection device includes data related to a nearbyvehicle. The received data from the collision detection device isanalyzed to determine that an accident is impending or occurringinvolving the vehicle (1106). Responsive to determining that theaccident is impending or occurring, the received data from the nearbyvehicle detection device is analyzed to detect an ID of the nearbyvehicle (1108). Additional data related to the nearby vehicle may alsobe determined (e.g., the position, direction of motion, speed,orientation, and/or contour of the nearby vehicle, etc.) (1110). Forexample, data from radar and/or lidar devices of the vehicle may beanalyzed to determine the additional data. The detected ID and theadditional data are stored in a storage device (1112).

The construction and arrangement of the systems and methods as shown inthe various embodiments are illustrative only. Although only a fewembodiments have been described in detail in this disclosure, manymodifications are possible (e.g., variations in sizes, dimensions,structures, shapes and proportions of the various elements, values ofparameters, mounting arrangements, use of materials, colors,orientations, etc.). For example, the position of elements may bereversed or otherwise varied and the nature or number of discreteelements or positions may be altered or varied. Accordingly, all suchmodifications are intended to be included within the scope of thepresent disclosure. The order or sequence of any process or method stepsmay be varied or re-sequenced according to alternative embodiments.Other substitutions, modifications, changes, and omissions may be madein the design, operating conditions and arrangement of the embodimentswithout departing from the scope of the present disclosure.

The present disclosure contemplates methods, systems and programproducts on any machine-readable media for accomplishing variousoperations. The embodiments of the present disclosure may be implementedusing existing computer processors, or by a special purpose computerprocessor for an appropriate system, incorporated for this or anotherpurpose, or by a hardwired system. Embodiments within the scope of thepresent disclosure include program products comprising machine-readablemedia for carrying or having machine-executable instructions or datastructures stored thereon. Such machine-readable media can be anyavailable media that can be accessed by a general purpose or specialpurpose computer or other machine with a processor. By way of example,such machine-readable media can comprise RAM, ROM, EPROM, EEPROM, CD-ROMor other optical disk storage, magnetic disk storage or other magneticstorage devices, or any other medium which can be used to carry or storedesired program code in the form of machine-executable instructions ordata structures and which can be accessed by a general purpose orspecial purpose computer or other machine with a processor. Wheninformation is transferred or provided over a network or anothercommunications connection (either hardwired, wireless, or a combinationof hardwired or wireless) to a machine, the machine properly views theconnection as a machine-readable medium. Thus, any such connection isproperly termed a machine-readable medium. Combinations of the above arealso included within the scope of machine-readable media.Machine-executable instructions include, for example, instructions anddata which cause a general purpose computer, special purpose computer,or special purpose processing machines to perform a certain function orgroup of functions.

Although the figures may show a specific order of method steps, theorder of the steps may differ from what is depicted. Also two or moresteps may be performed concurrently or with partial concurrence. Suchvariation will depend on the software and hardware systems chosen and ondesigner choice. All such variations are within the scope of thedisclosure. Likewise, software implementations could be accomplishedwith standard programming techniques with rule-based logic and otherlogic to accomplish the various connection steps, processing steps,comparison steps and decision steps.

While various aspects and embodiments have been disclosed herein, otheraspects and embodiments will be apparent to those skilled in the art.The various aspects and embodiments disclosed herein are for purposes ofillustration and are not intended to be limiting, with the true scopeand spirit being indicated by the following claims.

What is claimed is:
 1. A method of documenting an accident, comprising:receiving data from a collision detection device of a vehicle;determining, by a processing circuit, that based on the received data anaccident is impending or occurring involving the vehicle; generating arequest for a nearby vehicle to: illuminate a region associated with theaccident and actively acquire data related to the accident; and recordthe actively acquired data related to the accident; and transmitting therequest to the nearby vehicle.
 2. The method of claim 1, wherein thedata related to the accident comprises at least one of contour data,position data, velocity data, orientation data, and timing data.
 3. Themethod of claim 1, wherein the request specifies that the nearby vehiclerecord radar data related to the accident.
 4. The method of claim 1,wherein the request specifies that the nearby vehicle record lidar datarelated to the accident.
 5. The method of claim 1, wherein the requestspecifies that the nearby vehicle acquire radar data related to theaccident.
 6. The method of claim 1, wherein the request specifies thatthe nearby vehicle acquire lidar data related to the accident.
 7. Themethod of claim 1, wherein the request includes metadata related to thevehicle.
 8. The method of claim 7, wherein the metadata includespositioning coordinates of the vehicle.
 9. The method of claim 7,wherein the metadata includes a velocity and an orientation of thevehicle.
 10. The method of claim 7, wherein the metadata includescontact information related to an operator of the vehicle.
 11. Themethod of claim 7, wherein the metadata includes payment informationrelated to an operator of the vehicle.
 12. The method of claim 7,wherein the metadata includes a timestamp.
 13. The method of claim 12,wherein the timestamp is precise at least to a nanosecond.
 14. Themethod of claim 1, further comprising: receiving the data related to theaccident from the nearby vehicle, wherein the request directs the nearbyvehicle to transmit the data related to the accident to the vehicle; andstoring the data related to the accident in a storage device.
 15. Amethod of documenting an accident, comprising: illuminating and activelydetecting a nearby vehicle using a collision detection device of avehicle, wherein the collision detection device comprises at least oneof a radar device and a lidar device; receiving data from the collisiondetection device of the vehicle; analyzing, by a processing circuit, thereceived data to detect an impending or occurring accident, wherein theaccident involves the nearby vehicle; determining accident related datain response to the detected accident, wherein the accident related datais based on the received data; storing the accident related data in astorage device; and delivering the accident related data to the nearbyvehicle.
 16. The method of claim 15, wherein the accident related dataincludes timing information related to the nearby vehicle.
 17. Themethod of claim 15, wherein the accident related data includes dataregarding an additional vehicle associated with the accident.
 18. Themethod of claim 15, wherein the accident related data includes contourinformation related to the nearby vehicle.
 19. The method of claim 15,further comprising analyzing the received data to determine an ID of thenearby vehicle, wherein the ID includes a make and model of the nearbyvehicle, and wherein the collision detection device includes a camera.20. The method of claim 15, further comprising receiving a request torecord data related to the accident.
 21. The method of claim 20, whereindetecting the accident is responsive to receiving the request.
 22. Themethod of claim 20, further comprising delivering the accident relateddata to a source of the request.
 23. The method of claim 15, whereindetecting the accident is based on detecting a sudden velocity change inthe nearby vehicle.
 24. The method of claim 15, further comprisingencrypting the data related to the accident.
 25. The method of claim 15,wherein the data from the collision detection device is received at amaximum data rate in response to detecting the accident.
 26. A method ofdocumenting an accident, comprising: receiving data from a nearbyvehicle detection device of a vehicle, wherein the data includes datarelated to a nearby vehicle; receiving data from a collision detectiondevice of the vehicle; determining, by a processing circuit, that basedon the received data from the collision detection device an accident isimpending or occurring involving the vehicle; analyzing the receiveddata from the nearby vehicle detection device to detect an ID of thenearby vehicle; and storing the detected ID in a storage device.
 27. Themethod of claim 26, wherein analyzing the received data from the nearbyvehicle detection device to detect the ID and storing the detected IDare responsive to the determining that the accident is impending oroccurring.
 28. The method of claim 26, further comprising analyzing thereceived data to determine whether the nearby vehicle was involved inthe accident, wherein analyzing the received data from the nearbyvehicle detection device to detect the ID and storing the detected IDare responsive to determining that the nearby vehicle was not involvedin the accident.
 29. The method of claim 26, wherein the nearby vehicledetection device includes a camera and wherein the received data fromthe nearby vehicle detection device includes image data from the camera.30. The method of claim 29, wherein the ID of the nearby vehicleincludes a make and a model of the nearby vehicle.
 31. The method ofclaim 26, wherein the nearby vehicle detection device comprises an RFIDsensor, and wherein the ID of the nearby vehicle is based on an RFID tagof the nearby vehicle, and wherein the RFID tag includes at least one of(1) a license plate number of the nearby vehicle and (2) a make andmodel of the nearby vehicle.
 32. The method of claim 26, wherein thenearby vehicle is a vehicle to which a request was previouslytransmitted by the vehicle, and wherein the request is for the nearbyvehicle to: illuminate a region associated with the accident andactively acquire data related to the accident; and record the activelyacquired data related to the accident.
 33. The method of claim 26,further comprising analyzing the received data from the nearby vehicledetection device to determine additional data related to the nearbyvehicle, and wherein the additional data is stored in association withthe detected ID.
 34. The method of claim 33, wherein the additional dataincludes at least one of a location of the nearby vehicle, a speed ofthe nearby vehicle, and an orientation of the nearby vehicle relative tothe accident.
 35. The method of claim 26, wherein the collisiondetection device comprises the nearby vehicle detection device.